| Deep learning for time series forecasting: a survey JF Torres, D Hadjout, A Sebaa, F Martínez-Álvarez, A Troncoso Big Data 9 (1), 3-21, 2021 | 686 | 2021 |
| A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area DT Bui, ND Hoang, F Martínez-Álvarez, PTT Ngo, PV Hoa, TD Pham, ... Science of The Total Environment 701, 134413, 2020 | 372 | 2020 |
| Energy time series forecasting based on pattern sequence similarity F Martínez-Álvarez, A Troncoso, JC Riquelme, JS Aguilar-Ruiz IEEE Transactions on Knowledge and Data Engineering 23 (8), 1230-1243, 2011 | 345* | 2011 |
| Earthquake magnitude prediction in Hindukush region using machine learning techniques KM Asim, F Martínez-Álvarez, A Basit, T Iqbal Natural Hazards 85, 471-486, 2017 | 263 | 2017 |
| Multi-step forecasting for big data time series based on ensemble learning A Galicia, R Talavera-Llames, A Troncoso, I Koprinska, ... Knowledge-Based Systems 163, 830-841, 2019 | 259 | 2019 |
| Neural networks to predict earthquakes in Chile J Reyes, A Morales-Esteban, F Martínez-Álvarez Applied Soft Computing 13 (2), 1314-1328, 2013 | 246 | 2013 |
| A survey on data mining techniques applied to electricity-related time series forecasting F Martínez-Álvarez, A Troncoso, G Asencio-Cortés, JC Riquelme Energies 8 (11), 13162-13193, 2015 | 224 | 2015 |
| A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data MS Tehrany, S Jones, F Shabani, F Martínez-Álvarez, D Tien Bui Theoretical and Applied Climatology 137, 637-653, 2019 | 195 | 2019 |
| Coronavirus optimization algorithm: a bioinspired metaheuristic based on the COVID-19 propagation model F Martínez-Álvarez, G Asencio-Cortés, JF Torres, D Gutiérrez-Avilés, ... Big data 8 (4), 308-322, 2020 | 168 | 2020 |
| Earthquake prediction model using support vector regressor and hybrid neural networks KM Asim, A Idris, T Iqbal, F Martínez-Álvarez PloS one 13 (7), e0199004, 2018 | 163 | 2018 |
| A scalable approach based on deep learning for big data time series forecasting JF Torres, A Galicia, A Troncoso, F Martínez-Álvarez Integrated Computer-Aided Engineering 25 (4), 335-348, 2018 | 142 | 2018 |
| Big data analytics for discovering electricity consumption patterns in smart cities R Pérez-Chacón, JM Luna-Romera, A Troncoso, F Martínez-Álvarez, ... Energies 11 (3), 683, 2018 | 127 | 2018 |
| A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables J García-Gutiérrez, F Martínez-Álvarez, A Troncoso, JC Riquelme Neurocomputing 167, 24-31, 2015 | 119 | 2015 |
| Pattern recognition to forecast seismic time series A Morales-Esteban, F Martínez-Álvarez, A Troncoso, JL Justo, ... Expert systems with applications 37 (12), 8333-8342, 2010 | 119 | 2010 |
| Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula F Martínez-Álvarez, J Reyes, A Morales-Esteban, C Rubio-Escudero Knowledge-Based Systems 50, 198-210, 2013 | 117 | 2013 |
| Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure G Asencio–Cortés, A Morales–Esteban, X Shang, F Martínez–Álvarez Computers & Geosciences 115, 198-210, 2018 | 108 | 2018 |
| Medium–large earthquake magnitude prediction in Tokyo with artificial neural networks G Asencio-Cortes, F Martinez-Alvarez, A Troncoso, A Morales-Esteban Neural Computing and Applications 28, 1043-1055, 2017 | 106 | 2017 |
| A deep LSTM network for the Spanish electricity consumption forecasting JF Torres, F Martínez-Álvarez, A Troncoso Neural Computing and Applications 34 (13), 10533-10545, 2022 | 105 | 2022 |
| Seismic indicators based earthquake predictor system using Genetic Programming and AdaBoost classification KM Asim, A Idris, T Iqbal, F Martínez-Álvarez Soil Dynamics and Earthquake Engineering 111, 1-7, 2018 | 93 | 2018 |
| A novel imputation methodology for time series based on pattern sequence forecasting N Bokde, MW Beck, FM Álvarez, K Kulat Pattern recognition letters 116, 88-96, 2018 | 92 | 2018 |
Alicia Troncoso (ORCID: 0000-0002-9...Full Professor, Data Science & Big Data Lab, Universidad Pablo de Olavideupo.es의 이메일 확인됨
